Utilisations personnelles, professionnelles et pédagogiques des TIC par de futurs enseignants et des enseignants
Bibliographic record
Abstract
La recherche se penche sur les utilisations faites des TIC par des futurs enseignants et des enseignants. Traitées à partir du modèle de Raby (2004), les données révèlent que les utilisations personnelles et professionnelles des TIC faites par les futurs enseignants, peu importe leur année de formation, s’apparentent à celles des enseignants en exercice. En outre, une progression est notée dans les utilisations pédagogiques faites des TIC par les futurs enseignants et celles des enseignants en exercice. Seuls ces derniers font état d’utilisations pédagogiques qui s’inscrivent à l’étape d’appropriation, c’est-à-dire qui témoignent d’activités fréquentes réalisées dans un cadre d’apprentissage actif et significatif. Des pistes à suivre pour bonifier la formation initiale sont proposées.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".